I am a quantitative ecologist focused on identifying factors driving species distribution and population dynamics at local and global scale. I am broadly interested in exploring innovative methods for wildlife and biodiversity research and most of my recent work centers on new advancements in the collection, processing, and analysis of camera-trap data to inform wildlife conservation and management.
As a postdoc at the Yale Center for Biodiversity and Global Change, I aim at assessing the impact of human-induced stressors and landscape modifications on the occurrence of mammals and birds over large spatial and temporal scales and at identifying common traits among the species most vulnerable to human disturbance. I am also working on developing analytical tools to streamline the analysis of camera-trap data in Wildlife Insights and on promoting public sharing of camera-trap data by showing how it increases our knowledge of biodiversity at the global scale.
During my Ph.D. at the University of Minnesota, I demonstrated the importance of considering species-specific responses to survey design strategies when designing camera trap studies aimed at collecting data on multiple species simultaneously and showed how north American carnivores uniquely respond to different survey design strategies. I also focused on statistical methods to account for different sources of variability when analyzing camera-trap data, developed an R package to describe correlation structure in camera-trap and other binary datasets, and explored new approaches to estimate temporal activity patterns. While earning a BS in Biology and an MS in Eco-Biology at the Sapienza University of Rome, Italy, I studied how habitat fragmentation affects the ecology and population dynamics of ground-dwelling and arboreal small mammals and, as a postgraduate researcher at the Norwegian Institute for Nature Research (NINA) in Trondheim, Norway, I worked with GPS-telemetry data and data from scat sampling to explore how non-invasive sampling can provide information about the home range size of wolverines (Gulo gulo).
I greatly enjoy analyzing data and answering complex ecological questions, but I also know the joy and pain of fieldwork: I have deployed camera traps in the fantastic forests of northern Minnesota and checked nest-boxes and hair tubes, placed live-traps, and done radiotelemetry in some of the most beautiful parts of Italy. In the future, I plan to keep on investigating the ecological processes that govern the wonderful world in which we all live and that now more than ever requires our protection.
Iannarilli F, Erb J, Arnold TW, Fieberg JR. 2021. Evaluating species-specific responses to camera-trap survey designs. Wildlife Biology, online first [data and code
Archmiller A.A., Johnson A.D., Nolan J., Edwards M., Elliott L.H., Ferguson J.M., Iannarilli F., Vélez J., Vitense K., Johnson D.H. and Fieberg J. 2020 Computational Reproducibility in The Wildlife Society’s Flagship Journals. Journal of Wildlife Management, 84: 1012-1017. [data and code
Iannarilli F, Arnold TW, Erb J, Fieberg JR. 2019. Using lorelograms to measure and model correlation in binary data: Applications to ecological studies. Methods in Ecology and Evolution, 10: 2153 – 2162. [data and code
Specht HM, Reich HT, Iannarilli F, et al. 2017. Occupancy surveys with conditional replicates: An alternative sampling design for rare species. Methods in Ecology and Evolution, 8: 1725 –1734. [data and code
Scotson L., Johnston L.R., Iannarilli F., Wearn O.R., Mohd‐Azlan J., Wong W., Gray T.N.E., Dinata Y., Suzuki A., Willard C.E., Frechette J., Loken B., Steinmetz R., Moßbrucker A.M., Clements G.R., Fieberg J. 2017. Best practices and software for the management and sharing of camera trap data for small and large scales studies. Remote Sensing in Ecology and Conservation, 3: 158-172.